Monitoring Variance Change in Infinite Order Moving Average Processes and Nonstationary Autoregressive Processes

This article considers the sequential monitoring problem of variance change in stationary and non stationary time series. We suggest a CUSUM of squares procedure to detect variance change in infinite order moving average processes, and a residual CUSUM of squares procedure to detect variance change in non stationary autoregressive processes. Moreover, we introduce a bandwidth parameter to improve the monitoring power when change point does not occur at the early stage of monitoring. It is shown that both procedures have the same null distribution. The procedures are illustrated via a simulation study and an investigation of daily Mexico/US exchange rates.